def _save(self, results: Dict[str, Any], activation_name: ActivationName) -> None:
l, name = activation_name
preds_path = os.path.join(self.save_dir, f"{name}_l{l}_results.pickle")
model_path = os.path.join(self.save_dir, f"{name}_l{l}.joblib")
dump_pickle(results, preds_path)
joblib.dump(self.classifier, model_path)
def _save_results(
self, results_dict: Dict[str, Any], activation_name: ActivationName
) -> None:
if self.dc_config.verbose > 0:
for k, v in results_dict.items():
print(k, v, "", sep="\n")
print("Label vocab:", self.data_loader.label_vocab)
if self.save_dir is not None:
l, name = activation_name
results_path = os.path.join(self.save_dir, f"{name}_l{l}_results.pickle")
dump_pickle(results_dict, results_path)
def concat_pickle_dumps(self, overwrite: bool = True) -> None:
""" Concatenates a sequential pickle dump and pickles to file .
Note that this overwrites the sequential pickle dump by default.
Parameters
----------
overwrite : bool, optional
Set to True to overwrite the file containing the sequential
pickle dump, otherwise creates a new file. Defaults to True.
"""
activation_reader = ActivationReader(self.activations_dir)
for (layer, name) in self.activation_names:
activations = activation_reader.read_activations((layer, name))
filename = os.path.join(self.activations_dir,
f"{name}_l{layer}.pickle")
if not overwrite:
filename = filename.replace(".pickle", "_concat.pickle")
dump_pickle(activations, filename)
del activations